How AlphaBOLD Helped a Leading Healthcare Organization Turn a 45-Minute Review Into a 90-Second AI Workflow
Table of Contents
A nonprofit healthcare organization headquartered in Plymouth Meeting, Pennsylvania, develops trusted clinical resources used by healthcare professionals, patients, and organizations worldwide to support better care.
With that reach comes an important responsibility.
Organizations regularly request permission to use its guidelines, trademarks, and related content in their own materials. Each request must be reviewed to make sure those resources are represented accurately, used under the appropriate permissions, and presented according to established standards.
As demand grew, protecting that integrity became an increasingly time-intensive process.
Hundreds of Requests. Dozens of Checks. A Small Team
The organization was processing approximately 750 permission requests every month.
Each submitted document needed to be reviewed against detailed requirements covering trademark usage, naming conventions, licensing, guideline versions, and other usage standards. Some reviews also required checking references embedded within artwork or images.
The work required care, but many of the individual checks were repetitive.
A team of approximately five reviewers was handling the process manually, with each request taking around 30 to 45 minutes. At monthly volumes, that represented an estimated 375 to 562 hours of review work.
There was also a consistency challenge. When detailed rules are applied manually across hundreds of documents, review approaches and feedback can vary. There was no standardized record showing exactly what had been checked and why.
The organization needed a way to manage growing demand without compromising the quality and control required by the review process.
AlphaBOLD Built an AI Agent to Automate the Review Process
AlphaBOLD developed an AI-powered automation agent to provide a structured first pass within the existing permissions workflow.
Instead of requiring reviewers to start every request from scratch, the agent handles the repetitive preparation.
When a permission request arrives, the agent can:
- identify and read highlighted content within the submitted PDF
- apply trademark and usage rules
- verify applicable licenses and guideline versions
- interpret relevant content contained within artwork and images
- document findings in a structured validation report
- produce a marked-up version of the submitted document
- publish the results and notify the review team
The solution combines large language models with document and image understanding capabilities, all orchestrated within a broader automated workflow.
The agent is more than the AI model itself. It is the complete process surrounding it: receiving the request, understanding the document, applying the appropriate rules, documenting the findings, producing the required outputs, and returning the completed first pass to the review team.
Human reviewers retain final decision-making authority. The technology gives them a consistent, documented starting point so they can focus their time on exceptions, judgment, and final sign-off.
From 30–45 Minutes to Approximately 90 Seconds
The AI agent can complete its end-to-end first-pass workflow in approximately 90 seconds, compared with a manual baseline of 30 to 45 minutes per request.
20–30x faster processing
At approximately 750 requests per month, that represents an estimated 356 to 544 hours of processing capacity returned every month.
The agent pipeline can process approximately 40 requests per hour, compared with an estimated 6.7 to 10 requests per hour across the previous five-person manual workflow.
Just as importantly, every request can now begin with the same structured review process and documented findings that reviewers can inspect, verify, and act on.
What Agentic AI Looks Like When Built Around Real Work
This solution demonstrates where agentic AI can create meaningful operational value.
The agent does more than answer a question or summarize a document. It reads documents, interprets visual content, applies business rules, checks information, documents findings, generates files, publishes results, and hands the work back to a person for the decision that matters.
For this healthcare organization, that means protecting the integrity of widely used clinical resources while giving its team a more scalable way to manage the work required around them.
30–45 minutes → ~90 seconds
First-pass processing time
20–30x
Faster than the manual baseline
356–544 hours
Estimated processing capacity returned each month
750 requests
Supported at documented monthly volume
“AlphaBOLD helped us rethink a highly manual review process without taking people out of the decision-making loop. The AI agent gives our team a consistent, documented first pass on every request, allowing reviewers to spend more time on exceptions and final decisions instead of repetitive checks. The improvement in processing time has been significant, but just as important is having a more scalable and consistent way to manage growing request volumes.”
— BOLDcustomer
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